We investigate the use of multiple transmitting and/or receiving antennas for single user communications over the additive Gaussian channel with and without fading. We derive formulas for the capacities and error exponents of such channels, and describe computational procedures to evaluate such formulas. We show that the potential gains of such multi-antenna systems over single-antenna systems is rather large under independenceassumptions for the fades and noises at different receiving antennas.

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Capacity of Multi‐antenna Gaussian Channels

Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a software-defined radio, is defined as an intelligent wireless communication system that is aware of its environment and uses the methodology of understanding-by-building to learn from the environment and adapt to statistical variations in the input stimuli, with two primary objectives in mind: /spl middot/ highly reliable communication whenever and wherever needed; /spl middot/ efficient utilization of the radio spectrum. Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks. 1) Radio-scene analysis. 2) Channel-state estimation and predictive modeling. 3) Transmit-power control and dynamic spectrum management. This work also discusses the emergent behavior of cognitive radio.

/pdf/cognitive-radio-brain-empowered-wireless-communications-9m6gu0vz1z.pdf

Cognitive radio: brain-empowered wireless communications

Wireless Communications

What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.

What Will 5G Be

The global bandwidth shortage facing wireless carriers has motivated the exploration of the underutilized millimeter wave (mm-wave) frequency spectrum for future broadband cellular communication networks. There is, however, little knowledge about cellular mm-wave propagation in densely populated indoor and outdoor environments. Obtaining this information is vital for the design and operation of future fifth generation cellular networks that use the mm-wave spectrum. In this paper, we present the motivation for new mm-wave cellular systems, methodology, and hardware for measurements and offer a variety of measurement results that show 28 and 38 GHz frequencies can be used when employing steerable directional antennas at base stations and mobile devices.

Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!

Messages according to a method of wireless signal transmission are sent as sequences of unitary space-time signals. Each signal is representable as a matrix in which each column represents a respective transmitting antenna of a transmitting array, and each row represents a time segment. Each such matrix is proportional to a complex-valued matrix, all columns of which are mutually orthonormal. A new method for creating a constellation of signal matrices comprises providing an initial signal in the form of a complex, orthonormal matrix. The method further comprises generating a further plurality of matrices by a process that assures that each of the generated matrices is related to the initial matrix as a product of one or more multiplications of the initial matrix by one or more unitary matrices.

Wireless transmission method for antenna arrays using unitary space-time signals

A large scale antenna system (LSAS) entails a large number of base station (BS) antennas serving a much smaller number of terminals. LSAS demonstrates large gain in spectral-efficiency and energy-efficiency compared with conventional MIMO schemes. In the regime of infinite number of BS antennas, the performance of LSAS can be improved unboundedly by using a multi-cell cooperation method called pilot contamination precoding (PCP). As the number of BS antennas grows PCP completely cancels inter-cell interference resulted from unavoidable use of nonorthogonal pilot sequences in neighboring cells. In this paper, we consider downlink PCP design in the finite antenna regime, where besides pilot contamination, three other types of interference become prominent. We formulate the PCP design as maximizing the minimum signal to interference-plus-noise ratio (SINR) subject to network sum power constraint. We propose optimal and simple suboptimal algorithms for finding PCP matrices. We show that in a practical scenario, say with M = 100 antennas, these approaches give very significant improvement over conventional LSASs.

Pilot contamination precoding for interference reduction in large scale antenna systems

Channel propagation characteristics in a wireless communication system, wherein plural communication links or channels are defined between multiple transmit antenna elements and multiple receive antenna elements, are determined by selecting a matrix of training signals for transmission from the transmit antenna elements, and providing information concerning the selected training signal matrix to a system receiver. The training signals are transmitted from the transmit antenna elements to the receive antenna elements in a determined sequence during a defined training signal time interval, and signals corresponding to the training signals are received via the receive antenna elements. Components of a propagation characteristic matrix for use in discriminating signals transmitted at times other than the training signal time interval, are determined at the receiver as a function of signals received during the training signal time interval and the information concerning the matrix of training signals.

Determining channel characteristics in a space-time architecture wireless communication system having multi-element antennas

An apparatus for performance improvement of a digital wireless receiver comprises a processing circuit for processing a plurality of received signals and providing a processed signal, wherein a plurality of weights is applied to the plurality of received signals producing a plurality of weighted received signals. The plurality of weighted received signals are combined to provide the processed signal. A weight generation circuit generates the plurality of weights, wherein weights are generated so as to solve a minimization problem that penalizes excessive time variability in the weights.

Time-varying weight estimation

We analyze the capacity of a multiple-antenna wireless link with M antennas at the transmitter and N antennas at the receiver in a Rician fading channel when the channel is unknown at both the transmitter and the receiver. The Rician model is a nonstandard model with a Rayleigh component and an isotropically random rank-one specular component. The Rayleigh and specular components remain constant for T symbol periods, after which they change to completely independent realizations, and so on. To maximize mutual information over the joint density of T/spl middot/M complex transmitted signals it is sufficient to maximize over a joint density of min{T,M} real transmitted signal magnitudes. The capacity-achieving signal matrix is equal to the product of two independent matrices, a T/spl times/T isotropically random unitary matrix and a T/spl times/M real nonnegative diagonal matrix. If M>T, optimum signaling uses only T out of the M transmit antennas. We derive a novel lower bound on capacity which enables us to compute achievable rate regions for many cases. This lower bound is also valid for the case of purely Rayleigh-fading channels, where it has not been feasible, in general, to compute capacity, or mutual information. Our numerical results also indicate that the Rayleigh model is surprisingly robust: under our Rician model, up to half of the received energy can arrive via the specular component without significant reduction in capacity compared with the purely Rayleigh case.

Thomas L. Marzetta

Papers

Wireless transmission method for antenna arrays using unitary space-time signals

Pilot contamination precoding for interference reduction in large scale antenna systems

Determining channel characteristics in a space-time architecture wireless communication system having multi-element antennas

Time-varying weight estimation

Capacity of a mobile multiple-antenna wireless link with isotropically random Rician fading